Shale Gas, Wind and Water: Assessing the Potential Cumulative Impacts of Energy Development on Ecosystem Services within the Marcellus Play

Global demand for energy has increased by more than 50 percent in the last half-century, and a similar increase is projected by 2030. This demand will increasingly be met with alternative and unconventional energy sources. Development of these resources causes disturbances that strongly impact terrestrial and freshwater ecosystems. The Marcellus Shale gas play covers more than 160,934 km2 in an area that provides drinking water for over 22 million people in several of the largest metropolitan areas in the United States (e.g. New York City, Washington DC, Philadelphia & Pittsburgh). Here we created probability surfaces representing development potential of wind and shale gas for portions of six states in the Central Appalachians. We used these predictions and published projections to model future energy build-out scenarios to quantify future potential impacts on surface drinking water. Our analysis predicts up to 106,004 new wells and 10,798 new wind turbines resulting up to 535,023 ha of impervious surface (3% of the study area) and upwards of 447,134 ha of impacted forest (2% of the study area). In light of this new energy future, mitigating the impacts of energy development will be one of the major challenges in the coming decades.

[1]  M. Thring World Energy Outlook , 1977 .

[2]  Gene E Likens,et al.  Increased salinization of fresh water in the northeastern United States. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Liangying Hecker,et al.  Inter-regional transmission development for Eastern Wind Integration and Transmission Study , 2010, IEEE PES General Meeting.

[4]  Chris Mooney The truth about fracking. , 2011, Scientific American.

[5]  Thomas R. Schueler,et al.  Is Impervious Cover Still Important? Review of Recent Research , 2009 .

[6]  Amy Pocewicz,et al.  Frontiers inEcology and the Environment Development by design : blending landscape-level planning with the mitigation hierarchy , 2009 .

[7]  R. Kerr Energy. Natural gas from shale bursts onto the scene. , 2010, Science.

[8]  J. Wickham,et al.  Completion of the 2001 National Land Cover Database for the conterminous United States , 2007 .

[9]  Adrian Baddeley,et al.  spatstat: An R Package for Analyzing Spatial Point Patterns , 2005 .

[10]  Trevor Bailey,et al.  Statistical Analysis of Spatial Point Patterns. Second Edition. By PETER J. DIGGLE (London: Edward Arnold). [Pp. viii+159]. ISBN 0-340-74070-1. Price £40.00. Hardback , 2004, Int. J. Geogr. Inf. Sci..

[11]  Max Nielsen-Pincus,et al.  Predicting land use change: comparison of models based on landowner surveys and historical land cover trends , 2008, Landscape Ecology.

[12]  Margaret Rostker Energy Development and Wildlife Conservation in Western North America. , 2011 .

[13]  J. Evans,et al.  Gradient modeling of conifer species using random forests , 2009, Landscape Ecology.

[14]  A. G. Harris,et al.  Thermal Maturity Patterns (CAI and %Ro) in Upper Ordovician and Devonian Rocks of the Appalachian Basin: A Major Revision of USGS Map I-917-E Using New Subsurface Collections , 2008 .

[15]  Limin Yang,et al.  Development of a 2001 National land-cover database for the United States , 2004 .

[16]  J. Fargione,et al.  Energy Sprawl or Energy Efficiency: Climate Policy Impacts on Natural Habitat for the United States of America , 2009, PloS one.

[17]  P. Gilbert,et al.  Shale gas: a provisional assessment of climate change and environmental impacts , 2011 .

[18]  Raymond J. Kopp,et al.  Energy Resources and Global Development , 2003, Science.

[19]  T. Brown,et al.  Spatial Distribution of Water Supply in the Coterminous United States 1 , 2008 .

[20]  Sue Stolton,et al.  Running Pure: the importance of forest protected areas to drinking water: a research report for the World Bank / WWF Alliance for Forest Conservation and Sustainable Use , 2003 .

[21]  Robert P. Anderson,et al.  Maximum entropy modeling of species geographic distributions , 2006 .

[22]  Antoine Guisan,et al.  Predictive habitat distribution models in ecology , 2000 .

[23]  Joseph Kiesecker,et al.  Development by Design: Mitigating Wind Development's Impacts on Wildlife in Kansas , 2011, PloS one.

[24]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[25]  Thomas H. Kunz,et al.  Win-Win for Wind and Wildlife: A Vision to Facilitate Sustainable Development , 2011, PloS one.

[26]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[27]  R. King,et al.  A new method for detecting and interpreting biodiversity and ecological community thresholds , 2010 .

[28]  Z. Birnbaum,et al.  One-Sided Confidence Contours for Probability Distribution Functions , 1951 .

[29]  Lorne A. Greig,et al.  Scenario analysis in environmental impact assessment: Improving explorations of the future , 2007 .

[30]  Sheila M. Olmstead,et al.  Shale gas development impacts on surface water quality in Pennsylvania , 2013, Proceedings of the National Academy of Sciences.

[31]  J. Phillips,et al.  National geophysical data grids; gamma-ray, gravity, magnetic, and topographic data for the conterminous United States , 1993 .

[32]  Joseph Kiesecker,et al.  Wind and Wildlife in the Northern Great Plains: Identifying Low-Impact Areas for Wind Development , 2012, PloS one.

[33]  William M. Kappel,et al.  Water Resources and Natural Gas Production from the Marcellus Shale , 2009 .

[34]  T. Schueler The importance of imperviousness , 1995 .

[35]  J. Evans,et al.  Quantifying Bufo boreas connectivity in Yellowstone National Park with landscape genetics. , 2010, Ecology.

[36]  P. Barten,et al.  Forests, Water and People: Drinking water supply and forest lands in the Northeast and Midwest United States, June 2009 , 2009 .

[37]  Amy Pocewicz,et al.  Mapping Oil and Gas Development Potential in the US Intermountain West and Estimating Impacts to Species , 2009, PloS one.

[38]  Y. Wiersma,et al.  Predictive species and habitat modeling in landscape ecology : concepts and applications , 2011 .

[39]  R. King,et al.  Considerations for analyzing ecological community thresholds in response to anthropogenic environmental gradients , 2010, Journal of the North American Benthological Society.

[40]  Christopher A. Barnes,et al.  Completion of the 2006 National Land Cover Database for the conterminous United States. , 2011 .

[41]  D. Warton,et al.  Correction note: Poisson point process models solve the “pseudo-absence problem” for presence-only data in ecology , 2010, 1011.3319.

[42]  Robert Haining,et al.  Statistics for spatial data: by Noel Cressie, 1991, John Wiley & Sons, New York, 900 p., ISBN 0-471-84336-9, US $89.95 , 1993 .

[43]  J. Evans,et al.  Modeling Species Distribution and Change Using Random Forest , 2011 .

[44]  Pooya Soltantabar Annual Energy Outlook , 2015 .

[45]  Jürgen Symanzik,et al.  Statistical Analysis of Spatial Point Patterns , 2005, Technometrics.

[46]  Larry W. Canter,et al.  State of practice of cumulative effects assessment and management: the good, the bad and the ugly , 2010 .

[47]  Limin Yang,et al.  An approach for mapping large-area impervious surfaces: synergistic use of Landsat-7 ETM+ and high spatial resolution imagery , 2003 .

[48]  D. Rozell,et al.  Water Pollution Risk Associated with Natural Gas Extraction from the Marcellus Shale , 2012, Risk analysis : an official publication of the Society for Risk Analysis.

[49]  Robert Gilmore Pontius,et al.  Comparison of the structure and accuracy of two land change models , 2005, Int. J. Geogr. Inf. Sci..

[50]  Mehmet Erturk,et al.  Economic analysis of unconventional liquid fuel sources , 2011 .

[51]  Thomas F Cuffney,et al.  Responses of benthic macroinvertebrates to environmental changes associated with urbanization in nine metropolitan areas. , 2009, Ecological applications : a publication of the Ecological Society of America.

[52]  Jacob Cohen,et al.  The Equivalence of Weighted Kappa and the Intraclass Correlation Coefficient as Measures of Reliability , 1973 .

[53]  G. Wittemyer,et al.  Characterising the impacts of emerging energy development on wildlife, with an eye towards mitigation. , 2013, Ecology letters.

[54]  C. McDaniel,et al.  Increased Human Energy Use Causes Biological Diversity Loss and Undermines Prospects for Sustainability , 2002 .

[55]  B. Johnson,et al.  Rapid expansion of natural gas development poses a threat to surface waters , 2011 .

[56]  J. Abad,et al.  Impact of Shale Gas Development on Regional Water Quality , 2013, Science.